Hok Hei Tam
Co-Founder, Chief Technology Officer & Senior Principal Montai Therapeutics & Flagship Pioneering
Hok Hei Tam is Co-founder and Chief Technology Officer at Montai Therapeutics and Senior Principal at Flagship Pioneering. Hok Hei has distinctive expertise in chemical and bioengineering, informatics, and AI/ML; he has been a central architect of the Montai strategy to leverage AI/ML to decode untapped, diverse chemistry to develop breakthrough medicines for chronic disease. At Flagship, he has also co-founded 4 other companies that are using technology to drive solutions across human health and sustainability, including Sail Biomedicines and Invaio Sciences. Recently, he was also named to BioSpace’s inaugural 40 Under 40 list.
A named inventor on or author of more than 30 patent families and published papers, Hok Hei’s work has been published in top journals including PNAS, Nature Materials, Nature Biotechnology, and Nature Medicine. Hok Hei received a Ph.D. from MIT in chemical engineering and holds B.Sc. degrees in mathematics and chemical engineering from the Ohio State University.
Seminars
- Advanced AI is making it possible to discover new oral therapeutics for chronic disease and address significant unmet patient needs
- Montai Therapeutics’ CONECTA™ platform integrates proprietary bioassay data from a diverse chemical space and multimodal foundation models built on billions of chemical and biological datapoints
- This platform enables us to find diverse compounds inspired by nature’s chemical intelligence that can solve previously undruggable targets with the highest probability of becoming successful drugs
This industry leaders panel will discuss the small molecule industry collaborations and advancements shaping the space, key challenges to overcome, and where the biggest opportunities remain.
- Taking stock of the strengths, weaknesses, opportunities and threats (SWOT) of AI/ML-derived small molecules
- What advancements in AI/ML x med chem x computational convergence should we be most excited about?
- How do you perceive the AI/ML-derived small molecule space? How has industry sentiment changed in the last 12 months?
- What are the technical or scientific bottlenecks that are slowing AI/ML-derived small molecule discovery?
- What are the most reliable and experimentally validated use cases for AI/ML-methods that are being integrated into the small molecule discovery funnel? And which use cases for small molecule discovery remain challenging to get right?
